Lead Machine Learning Engineer
Agile Resources, Inc. - Cleveland, Ohio, us, 44101
Work at Agile Resources, Inc.
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Overview
Hybrid Remote in Cleveland, OH 44139 (i.e., 4 days onsite/week) Compensation:
up to $160k salary/year + 7% salary = up to $171k total compensation/year 100% company paid medical benefits (for you + your family) dental, vision, LTD/STD, HSA/FSA, term life, supplemental health insurances (e.g., Aflac) 12-weeks paid parental leave 401(k) + 3% company match Unlimited PTO Project & Role Overview: We're looking for a Lead ML Engineer to develop, implement, and manage innovative, data-driven ML solutions and machine learning models. You'll be the first hire on a new, standalone ML team, working directly with the Director of Data Engineering. Your initial and primary focus will be on developing machine learning pipelines and establishing the foundational ML ecosystem. This team is expected to grow, with the potential to add a second engineer within a few months, and this role offers a clear pathway to becoming a formal team manager. In this highly hands-on role (approximately 75-80% hands-on initially), you'll collaborate across departments to build cutting-edge solutions that enhance decision-making and optimize performance. Responsibilities: Work directly with the Director of Data Engineering and meet with the broader data engineering team to understand requirements and technical needs. Design and implement scalable ML models and algorithms aligned with business objectives. Lead model development, pipeline implementation, and integration with various data platforms. Develop high-performing, reusable, and reliable code following industry standards and best practices. Participate in all phases of the Software Development Life Cycle (SDLC), including requirement gathering, design, implementation, testing, deployment, documentation, and support. Build robust machine learning pipelines leveraging tools such as Python, PySpark, and Databricks. Collaborate with data analysts, data engineers, software engineers, and business analysts to translate complex business requirements into technical solutions. Employ DevOps practices (including GitHub and CI/CD tooling) to ensure proper version control and adherence to best practices. Troubleshoot, analyze, and resolve AI model performance issues and production problems. Maintain up-to-date knowledge of advancements in machine learning and data engineering. Actively participate in team meetings, contributing ideas and insights to drive continuous improvement. Demonstrate strong problem-solving skills, excellent work ethic, and a proactive attitude. Perform code reviews and help set technical direction for the team. Collaborate with leadership on architecture and roadmapping for the evolving AI ecosystem. Basic Qualifications: Bachelor’s degree or higher in Computer Science, AI, Data Science, or a related field, or equivalent experience. 3+ years of hands-on experience developing and deploying machine learning solutions. Strong experience with Azure Machine Learning (Azure ML) is highly preferred. This includes building ML pipelines (data ingestion, transformation, model training, deployment), utilizing the model registry and tracking features, and conducting experimentation via Azure ML Studio or SDK. Proficiency in Python programming (Spark, pandas, etc.) and SQL. Experience with Visual Studio, Git (specifically GitHub), and DevOps methodologies. Familiarity with software development fundamentals such as SOLID principles, Object-Oriented design, DRY, and Domain Driven Design. Strong communication skills, both written and verbal. Preferred Qualifications: Prior experience as a Data Engineer or Data Analyst is a plus. Experience with other Azure technologies such as Azure Synapse, Azure Data Factory (ADF), Azure Functions, Azure Databricks, Azure SQL, and Cosmos DB. Experience with PySpark and Databricks. Knowledge of Airflow for workflow orchestration. Experience with Blob Storage for data lake use cases. Knowledge of Vibe Coding and familiarity with cutting-edge industry trends. Exposure to Agile methodologies and Test Driven Development (TDD). Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
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